Data cubes are implemented in techniques used in various data management applications. A data cube, as used herein, refers to an array of measures (for example, total sale, number of customers, etc.) for a given set of values of a set of dimensions (for example, city, item, year, etc.). By way of example, data cubes can be used to determine the number of customers for every possible value of state and age (wherein, for example, the state equals California and the given age equals 26). Commonly, users of data cubes are interested only in cube entries satisfying some iceberg conditions defined over support, recall, precision, or some aggregate measure. As used herein, an iceberg cube refers to a cube which satisfies some condition over an aggregated measure. An example might include the number of customers for every state and age if the number of customers is more than 10.
Cube aggregations are commonly performed on pre-specified dimensions and hierarchies corresponding thereto. For ordered attributes (which can take continuous values), users may not define (and/or may not wish to define) any hierarchy. For example, for performing aggregations over age, it may not be desirable to divide the domain in pre-specified age ranges (0-10, 10-20, etc.). Rather, it may be desirable to identify the ranges which satisfy the iceberg conditions.